In the beginning of the quarter, I introduced the topic of communication and emphasized the beauty of its intricacies. On an everyday basis we may take communication for granted and brush it off with little notice; we fail to acknowledge and appreciate how incredibly complex it is. When talking to a friend or calling out to a loved one, we do not think about the years and years of evolution that have molded our communication systems into the efficient system it is today. The environment is always changing such that the world of our ancestors was much different than ours at present day. We face and are presented with many different factors, and Endler reminds us that it is these “factors that affect signals [. . .] constrain or bias the direction of evolution of signals and signaling systems” (Endler, 1993). As I mentioned in my first post of the quarter, the phylogenetic history of a species works hand in hand with the geological time a clade spends in the signaling environment to produce a specific type of signaling design, thus evolving to increase the efficacy of transmission of the message between emitter and receiver.

The first example I discussed was that of the honeybee. Their waggle dance proved useful during their careers as foragers such that they could use location information acquired from the dance to find the indicated food source which in turn contributed to the foraging success of a honey bee colony” (Biesmeijer & Seeley, 2005). We saw, however, that not all bees used the used the waggle dance in the same manner. Honeybees were more like to use information obtained through a waggle dance if they failed to find food on their previous trip or if they were a novice, foraging for the first time. Therefore, the waggle dance was not just a simple communication system utilized by all. Instead, its usefulness was determined by the characteristics and factors revolving around the recipient. From Biesmeijer and Seeley’s article, we saw how the value of certain communication systems can differ depending on the situation. We cannot state a communication system’s benefit in simple terms.

We then waltzed our way into the discussion of another type of honeybee dance, the shaking dance. Although the purpose of this dance was unknown, Gahl found that of the 44.8% of the bees that danced atop another, 96% of the bees danced on a honeybee that was younger than themselves. The majority of the shakers were 9-19 days old and the bees shaken were mostly 2 days old, showing some sort of discrimination by age. From this, Gahl illustrated how communication can have these types of discriminations between the recipient and producer. Communication is not always general across a whole species. Instead, the recipient and producer often times hold certain relationships, which affect the type of communication. We see this in humans as well. For most cultures, we speak differently towards our elders in comparison to those the same level as us or even younger than us. We communicate with different levels of respect depending on if we are talking to our boss, our family, or an aquaintance. Communication is not straightforward but instead depends on certain discriminations.

Then, from honeybees we transitioned to monkeys and discussed the systematic use of distinguishing signals that represented a distinction of objects and a sorting of objects into groups. We focused specifically on predator classification of vervet monkeys through their acoustically different alarm calls to at three different predators: leopards, martial eagles, and pythons (Seyfarth et al. 1980). Upon hearing the different calls that indicated a specific type of predator, the monkeys responded in a specific and respective manner that “seemed to represent adaptive strategies for coping with the hunting behavior of the predators involved” (Seyfarth et al. 1980). Leopard alarms caused monkeys to run up into the trees, eagle alarms caused monkeys to run into a dense bush for cover, and snake alarms caused monkeys to look down towards the ground for their predator. They responded “as though each type of alarm call designated different external objects or events” (Seyfarth et al. 1980). Therefore, this systematic use of signals means that the animals must understand contextual communication cues. An alarm signal can elicit general behavior to remove oneself from danger. However, vervet monkeys show much more complex behavior; they have to know how exactly to remove themselves from danger by knowing what type of danger they are in. Through this article, the importance that both the producer and the recipient must share similar knowledge was illustrated, otherwise this type of communication would fail and would not be as beneficial to the species. The results revolving around younger vervets further supported this point. They did not encompass as much knowledge as their adult counterparts; there was a difference in the amount of information and experience between recipient and caller. Therefore, they made false alarms to twigs and harmless shadows, proving to be inefficient at such calls.

We then went from identifying types of predators to identifying oneself in the bottlenose dolphins. The distinctive calls, unique on the level of the individual, was shown to be encoded by the pattern of frequency modulation that gave a spectrographic contour its distinctive shape (Janik et al., 2006). Janik et al. showed that such calls did not rely on specific voice features on the individual, but instead depended on the shape of the call itself. This revealed the power of communication stripped down to its basic form. Just the frequency pattern alone can achieve, at least in some species like the bottlenose dolphins, very efficient communication means.

The last two articles we discussed looked at communication in King Penguins and the search for their respective mates. The first of the two commented on the efficacy of their communication. An astounding 70.17% of the land partners were able to discriminate the very first call of their returning mate, and the average distance between the two was found to be 8.3 meters. This proved to be a very impressive feat taking into consideration how massive and extremely dense the colonies were. The second article took it a step even further, and their results showed that penguins actually alter their communication mean depending on the weather. With windier conditions, penguins increase their call duration and number of syllables, even taking into account the direction of the wind (upwind or downwind). Lengagne et al. referred to this as a “redundancy process” where the probability of successful communication may be increased by repeating the same information many times. Therefore, we saw how communication is not a simple and straightforward output-input system. It, along with almost all types of communication, is extremely dynamic and sensitive to many variables that affect the modality, efficiency, and characteristics of communication.

From all these articles, we can now appreciate and admire specific examples reflecting the beauty of communication. Animal studies allow us to delve into our own world and perhaps better understand how complex human communication is as well. There are many types of forms, strategies and modes that have been tweaked and are still being perfected for the present environment. One type of communication might prove to be beneficial to one species or in one context but not so in another. There is a unique interplay between many factors, but overall, like the common saying goes, communication is key!

The previous blog introduced us to the difficulties penguins face when trying to find their mates amongst their crowded colony. As a reminder:

A bird returning from the ocean [. . .] goes back to the breeding area and then calls its mate using the mutual display call. The partner, incubating the egg or rearing the chick, responds and thus gives its identity and its exact position in the colony. After a few calls, the two individuals are able to find each other. [. . .] Colonial life requires that vocal recognition occurs in the continuous background noise of the colony (Lengagne et al., 1999).

The above research was conducted during dry, calm weather. However, the natural conditions are hardly so. Instead, penguins spend much of their lives trying to survive in windy, arctic conditions and are continuously subjected to the influence of strong polar wind streams. Lengagne, Aubin, Lauga, and Jouventin have continued their research to look at if penguins have adopted some sort of adaptation to account for varying weather conditions, and if so, how they accomplish such a feat.

They propose that penguins take advantage of the mathematical theory of communication as follows. The volume of information (V) contained in a produced signal is equal to the signals frequency (F), times the signal duration (T), times the log of one plus signal to noise ratio (g=log2(1+S/N)) such that V=FTg. Because windy conditions decrease the amount of volume information transmitted by decreasing the signal to noise ratio, the producing signal must be modified to counteract such degradation. It is assumed that penguins are already emitting signals at their maximum amplitude and therefore cannot directly increase their signal to noise ratio. Instead, it is hypothesized that penguins increase their signal duration (T) in two ways, “birds can extend the duration of the mutual display call or enhance the emission rate of the call” (Lengagne et al., 1999).

They measured the percentage of the total energy in each category (taken from the middle of the colony) via Welch’s method of 80-second recordings. The independent variable was presence of wind such that analyses were made in conditions with no wind and conditions with a wind speed of 11 meters per second.

Secondly, the entropy of broadcast calls was computed in the following three conditions. Control conditions were taken as trails where wind speeds were 5 meters per second or less. Accelerated wind conditions were taken as trials where wind speeds were 11 meters per second. These high-speed conditions were studied in two ways: with the direction of the wind favorable to the transmittance of calls or with the direction of the wind opposing the transmittance of the calls. In this part of the experiment, Lengagne et al. were interested in the “emergence of the penguin’s signal over the background noise (colony+wind) [. . .] measured by computing the entropy of the distribution of its energy” via a calculation proposed by Beecher in 1988 (Lengagne et al., 1999).

Thirdly, Lengagne et al. measured the number of syllables and call durations in six different categories: 5, 6, 7, 8, 9, and 11 meters per second, all at a direction opposing propagation.

Fourthly, the number of calls emitted by the returning penguins was observed in the same categories discussed in the second part of their experiment.

And lastly, Lengagne et al. used the time duration required for change-over as a means to assess the wind-cost for penguins.

Quantitatively, they found that for windy conditions, 23.8% additional energy corresponded to physical noises such as wind (which intuitively makes sense) and the distribution of energy corresponding to the calls of penguins and noises from the colony decreased.

From the second part of their experiment, Lengagne et al. found that the aforementioned observations had correlations with the amount of entropy of the broadcast calls. Downwind conditions are correlated to wind direction favorable to the signal propagation while upwind conditions are correlated to wind direction against signal propagation. As noted in the caption, “a value near 1 characterize[d] a signal almost lost in the background noise” (Lengagne et al., 1999). It can be seen that in windy situations with the wind going against signal propagation, most of the signal is lost due to the background noise (again, agreeing with intuition).

When looking at the number of syllables and call duration, the “two separate models are in surprisingly good agreement with the values of their respective wind speed threshold, W,” duration of call being 7.70 meters per second and 7.52 meters per second for number of syllables (Lengagne et al., 1999). Above those two thresholds, the data fits a linear graph with positive slopes as follows:

In the fourth part of their research, they found that in the upwind condition, the number of calls emitted by both the returning and the brooding penguins were 11.6 calls, which exceeded that of the downwind condition (7.7 calls) and that of lack of wind (5.3 calls) with statistical significance.

To quantitatively show the cost of windy environments, Lengagne et al. showed that when graphing the duration of change-over versus wind speed, the difference between the slopes of the regression lines were statistically significant “showing that the time necessary for change-over was more important in windy situations than without wind” (Lengagne et al., 1999).

The data found by Lengagne et al. shows that the modality of emission of penguin calls changes as wind speed increases. Wind increases the environmental ambient noise which affects both the amount of information transmitted and the distance over which the information is transmitted such that an increase in background noise leads to a diminution of the signal to noise ratio. Sometimes, the “attenuation becomes so strong, the signal disappears” (Lengagne et al., 1999). In order to account for such attenuation and increase the success of their signals, penguins increase their call duration and enhance the number of syllables within each call. Overall, the total number of calls between the mates increases as well. These results are linked to an increase in the “redundancy process” where, “by repeating the same information many times, the birds may increase the probability of communicating during a short-window during which the wind speed suddenly drops” (Lengagne et al., 1999). In other words, an increased redundancy in penguin signaling increases the probability of receiving the intended message. Such an acoustic adaption supports the finding that the animal adjusts its behavior in response to wind noise, at least in the temporary sense. The penguin “adapts in some manner to wind speed and wind direction or noise generated by the wind or indirectly some other parameters linked to the wind modifying the number of syllables that must be emitted” (Lengagne et al., 1999). It is fascinating to see how communication is not static, but a dynamic process that take into consideration many inputs at the current situation. Communication, therefore, is not just an output system that is straight forward. It’s sensitive to many variables such that the efficiency of communication can be enhanced.

Lengagne, T., Aubin, T., Lauga, J., & Jouventin, P. (1999). How do king penguins (Aptenodytes patagonicus apply the mathematical theory of information to communicate in windy conditions?. Proceedings of the Royal Society of London. Series B: Biological Sciences, 266(1429), 1623-1628.

As the holiday season rolls in full swing and the festivities begin, Christmas decorations become delightfully impossible to avoid. Snowmen, gingerbread families, doves, and penguins seem to pop-up everywhere amongst decorated Christmas trees, wreaths, and lights. To keep with the spirit of the season, my blog this week will revolve around those mini-tuxedo dawning creatures, the penguins.

During three months out of the year, king penguins alternate care duties on land with foraging trips on the sea between mates. However, king penguins live in extremely large colonies consisting of anywhere from a few hundred to 500,000 mating pairs, which poses a major problem. Upon returning from sea, finding a single penguin in such a massively dense crowd, about 2.2 breeders per square meter, seems nearly impossible. To make matters more difficult, king penguins lack a nest. Instead, the mate on land incubates the egg on his feet, allowing him to move within the colony during storms or disputes with neighbors. The resulting “short distance movement [. . .] creates an important problem in relocating one’s mate” (Lengagne et al., 1999). The work of Lengagne, Jouventin, and Aubin aimed to study how penguins are able to handle such a problem and have found that the “difficulty in relocating mates posed by wandering incubation has been partially solved by the use of acoustic signals” (Lengagne et al., 1999). Acoustic calls are first produced by the returning penguin as he aims to identify his mate. His mate calls in reply, providing more information on her location within the colony. They repeat this process until they are reunited. In addition to the aforementioned, each pair faces difficulties due to their environment. Not only do windy and snowy conditions drown out and degrade the sound of their calls, but the background noises due to conspecific calls with similar temporal and spectral characteristics from other calling penguins generate an extreme jamming effect.

Lengagne et al. observed 28 pairs marked for individual identification from the laying of their egg to the end of the brooding stage (when both parents leave the chick to forage for food). The calls of each individual of interest were recorded. While one of the penguins were out foraging for food, the calls of that absent penguin were played to its mate at a distance of 20, 15, 14, 13, 12, 11, 10, 9, 8, and 7 meters away in a randomized fashion. It is important to note that the calls were played back in the morning during calm and dry weather. They then noted the response of the penguin and categorized them either as positive (where the penguin calls in reply to the broadcast signal of its absent mate, interpreted as recognition of its mate’s signal) or negative (where there is no vocal response and the penguin fails to reply, interpreted as failure to discriminate the broadcast signal of its absent mate). They also observed what they termed the Distance of First Emission, or the distance between the two penguins at the beginning of the acoustic search when the first call by the returning penguin was made. They kept track of the Number of Display Calls emitted by the Arriving and Incubating penguins, termed NCA and NCI, in addition to the Time Delay, or the time taken between the first call of the arriving penguin and the moment of unification.

Lengagne et al. found that 71% of the incubating or brooding penguins moved, on average, a distance of 4.4 meters while their mate was away foraging (total, combining the results from both the incubating and brooding stages). Transforming this linear distance into the maximum radius of circular areas produced an area of presence of 65.7 meters squared. Within this area, the number of mating pairs was estimated to about 145.

They also found the average discrimination distance to be 8.8 meters such that at 8.8 meters, the penguins called back in response to their returning mate indicating that there was recognition of the initial call.

The average distance between the two penguins when the returning penguin made his first call was 8.3 meters.

Lengagne et al. found that there were strong correlations between Time Delay and the DFE, between the NCA and DFE, and the NCA and Time Delay.

The data showed that the returning penguins called an average of 5 times over an average time of 114 seconds to reunite with its partner, and 70.17% of the time, its partner was able to discriminate the very first call of the returning penguin.

Lengagne et al. discuss how the efficiency of these uniting calls is accomplished. The returning penguin “progresses silently towards a preferred area of the colony, named the attachment zone, probably using topographic cues” then starts its acoustic search (Lengagne et al., 1999). However, because the individually specific calls propagates among the bodies and background noise of thousands of penguins, the broadcast distance is reduced, the signal degrades, and masking effects alter the frequency and temporal domains of the calls, which all ultimately impairs the communication process. However, the fact that the majority of the incubating king penguins discriminate their incoming mates at their first emission implies that acoustic communication is a particularly efficient strategy in this species” (Lengagne et al., 1999).

One thing to bring up, though, is the distinction limitation of observing performance. Just because the penguin does not respond to the returning bird (negative response) does not mean that it does not recognize its partners call. Maybe the penguins hear their mates’ calls, however it takes energy to call back out to them (they don’t have much energy taken that they haven’t eaten for so long while their mates are out obtaining food). Therefore, even if they hear that their mate is far away, they could wait a little longer until they know their mate is close enough so it is more likely they will be reunited. It could be argued that this increases efficiency and energy utilization. In addition, there is a difference between hearing their mates call as opposed to recognizing it. The distance of 8.8 meters relates to a clear, calm, and dry environment where the main variable would be recognition. However, if the environment were snowy or windy, it becomes an issue of whether or not the penguins can even hear each other in the first place.

Another thing of discussion revolves around their methods. At what loudness did they play back the calls? Although they played the calls at set distances, maybe the loudness they played it out actually corresponded to a different distance. For example, if they played the recorded call back too loudly, having the speaker 11 meters away could actually be interpreted as the penguin being only 9 meters away.

Lengagne et al. looked at how far away the returning bird is from the brooding penguin once the brooding penguin calls back, indicating recognition by the brooding penguin. However, I am curious to know if this is the same distance required for the returning bird to recognize the calls of the brooding bird. Maybe there is something about moving around (by the returning penguin) that makes it different when compared to staying in one general location (the brooding penguin) in regards to hearing and recognizing calls. When all is said and done, however, this is still an amazing feat penguins accomplish each year.

To obtain a better understanding of the difficult situation penguins are faced with, please see the following video at 1:00 (1:00 on will show you how noisy and crowded the colonies are):

Attached are some pictures illustrating just how densely populated the penguin colonies are. The difficulties of finding ones mate can further be appreciated.

Like that of monkeys, the brain of another animal is thought to be comparable to the brain of humans. Dolphins are commonly labeled as “smart,” and their levels of intelligence have made them a popular animal of study. V. Janik, L. Sayigh, and R. Wells followed this trend and conducted their research on the identity calls of bottlenose dolphins. Identity information, for almost all animal calls, give specific details of species, population, group, family line, and even in some cases individual identity (Janik et al. 8293). However, dolphins use distinctive calls unique on the level of the individual. Individual identity information requires a tremendous amount of interindividual variability and is hypothesized to be encoded by the “pattern of frequency modulation over time that gives a spectrographic contour its distinctive shape” (Janik et al. 8293). Janik et al. however addressed the problem of whether this type of individual discrimination occurs dependently of voice features. For example, human naming is accomplished dependently of voice features. You could recognize your name if you heard it in your own voice, in your friend’s voice, or in a stranger’s voice. We recognize that identity call based on the name itself and not on the voice. Dolphins can use distinctive call types as descriptive labels in referential communication, however, the research of Janik et al. aimed to see how dolphins do so.

Janik et al. produced “synthetic whistles that had the same frequency modulation but none of the voice features of known signature whistles” in the following manner (Janik et al. 8293). They recorded adult dolphins and transformed their calls into a synthetic form via SIGNAL 3.1, a program that essentially stripped down the whistles to its basic frequency modulation pattern. Then, over four seasons between June 2002 and February 2005, they played back these calls and measured the target dolphins’ responses. Each animal was held in a net by several people such that the dolphin’s head was free to move from side to side. Fifteen minutes after the dolphin became acclimated to the aforementioned position, the speaker was introduced 2 meters to the side and the calls were played. Each subject was exposed to a “sequence of synthetic whistles resembling the signature whistle of a related individual (as determined through long-term observations and confirmed through genetic testing) and a sequence of synthetic whistles resembling the signature whistle of an unrelated but known individual” (Janik et al. 3296). To avoid confounds, the calls were matched between the related and non-related individuals on the levels of approximate age, sex, and time spent together. Any head turn that was greater than 20 degrees was counted as a turn related to the call. (Head turns less than 20 degrees were not counted since dolphins naturally move their heads back and forth within this range).

The results of Janik et al. demonstrated that “bottle nose dolphins from Sarasota can recognize structure whistles of individuals [. . .] [through] distinctive frequency modulation patterns [dependent of] voice features” (Janik et al. 8295). Individual dolphins turned their head more towards the speaker if the playback was the synthetic signature whistle of a close relative rather than that of an unrelated individual. The whistle modulation contour themselves therefore carry the identity information required. They addressed the possibility that related dolphins had more similar whistle calls than unrelated dolphins as follows. Janik et al. tested to see if the response strength of targeted dolphins responded related to stimuli significantly more or less similar to their own whistle, independent of kin relationship, and found no significant differences (Janik et al. 8295). Therefore, the orienting responses of the dolphins were not due to similarities to their whistle.

As stated before, individual identity information is encoded independent of the signaler’s voice or location such that the frequency modulation pattern of signature whistles is sufficient for individual discrimination (Janik et al. 8295). It does not mean, however, that dolphins do not have or benefit from voice features specific to each individual. In their discussion, Janik et al. suggest that their findings support the notion that dolphins are recognizing whistles as opposed to merely discriminating between them. They define recognition as “perceiving something to be identical with something previously known,” and discrimination as “the comparison of distinctive features that can use, but does not require, such previous knowledge” (Janik et al. 8295). Therefore, this reveals the complicated abilities dolphins encompass.

I would like to just address one concern. When they tested the dolphins, they were constraining the subject in an unnatural manner. Dolphins are free-swimming animals, and I wonder if such methods caused any distress which could therefore alter any results.

In closing, the following is a pictorial representation of the dolphin whistles. The left side shows the natural original whistles while the right side shows the corresponding synthetic versions.

According to Robert Seyfarth, Dorothy Cheney, and Peter Marler, the semantics of animal communication is a “central but neglected issue” (Seyfarth et al. 801). Therefore, they conducted research on predator classification to provide the necessary attention to such matters. Their focus was on the systematic use of distinguishing signals which represented a distinction of objects and a sorting of objects into groups. Essentially, they wanted to see how animas “categorize” objects in their external world, specifically speaking, how free-ranging vervet monkeys categorize predators. In order to do so, they studied three groups of vervet monkeys comprised of adult males, adult females, juveniles, and infants. Previous studies showed that vervets give “acoustically different alarm calls to at least three different predators: leopards, martial eagles, and pythons” in the following manner (Seyfarth et al. 802).

Leopard: short, tonal calls produced in a series on both exhalation and inhalation

Eagle: low-pitched, staccato grunts

Snake: high-pitched, stutters

These alarm calls were distinct from nonalarm vocalizations and associated with different types of vervet monkey responses. Alarm calls produced by separate vervet monkeys were recorded previously. Through a hidden speaker, Seyfarth et al. presented each type of alarm call to the groups of monkeys and observed their reactions. (By using a speaker, they eliminated the confound of monkeys reacting due to visual cues or sightings of the predator.) Equal presentations of each alarm were played in a systematically varied fashion. Fifty trials were conducted when monkeys were on the ground, and thirty-eight trials were conducted when the monkeys were in trees.

From the table, we see that these responses were specific to each alarm presented and “seemed to represent adaptive strategies for coping with the hunting behavior of the predators involved” (Seyfarth et al. 802). When leopard alarms were played, the monkeys most often ran up into trees. In a natural setting, this would locate them in an area safe from the ambush style of attack characteristic of leopards. When eagle alarms were played, the monkeys most often looked upward, ran into dense bushes for cover, or executed both behaviors. In a natural setting, this would allow the monkeys to avoid attacks from the air. When snake alarms were played, the monkeys most often looked down towards the ground, which in a natural setting, would allow them to locate and avoid their predator (Seyfarth et al. 802). For all calls, all monkeys looked toward the speaker, the source of the alarm, and scanned their surroundings as if searching for additional cues; they responded “as though each type of alarm call designated different external objects or events” (Seyfarth et al. 802).

Therefore, Seyfarth’s et al. findings (that acoustically distinct alarms were assigned to different predators) support the notion that vervet monkeys can effectively categorize other species, particularly their predators. What’s interesting is that there is an age discrimination for this behavior. Adults were the most selective such that leopard alarms were primarily performed to leopards, eagle alarms to eagles, and snake alarms to pythons. Younger monkeys, however, did not distinguish between the different predators as well as adult monkeys did. According to Seyfarth et al., infants gave leopard alarms to a wide range of terrestrial mammals, eagle alarms to many different kinds of birds, and snake alarms to snakes or long objects on the ground, therefore failing to distinguish between particular predator species within such classes (Seyfarth et al. 802). In addition, young monkeys were more likely to give alarms to things that posed no danger. However as they matured and gained more experience they “sharpened the association between predator species and the type of alarm call” (Seyfarth et al. 803).

The findings of Seyfarth et al. are interesting because this systematic use of signals means that the animals must understand contextual communication cues. An alarm signal can elicit general behavior to remove oneself from danger. However, vervet monkeys show much more complexed behavior; they have to know how exactly to remove themselves from danger. It brings into discussion discriminative stimulus, where the specific type of alarm call is the discriminative stimulus, and the response outcome relationship varies. If the wrong response is performed based on the context, they will not effectively avoid the predator and therefore will not experience a desired outcome. However, if the alarm call is different, that same response can allow avoidance of the predator and produce a desire outcome. It all depends on the discriminative stimulus, or specific alarm call, that is produced by the vervet monkeys.

Popular shows such as So You Think You Can Dance and Dancing with the Stars have illustrated that there is an extremely wide range of dancing styles. From samba to ballet, and hip hop to tap, there are many forms of dancing in which humans engage. Similarly, honeybees have multiple forms of dancing that they use throughout their lives. Last week we discussed the waggle dance, however this week’s focus will be the shaking dance. Robert Gahl describes the shaking dance as a dorsal-ventral abdominal vibration of the honeybee by means of rapid contractions of leg muscles and pivoting of the legs (Gahl, 230). This dance, enacted by worker bees, can be performed alone, on top one other bee, or atop several bees. A previous study done by Allen, M. indicated that, for dances atop other honeybees, there is no age relationship between the shaker (intiator of the shaking dance) and the bee shaken. In other words, the individual shakers did not tend to shake a particular age-range of worker bees. Contrastingly, Gahl found just the opposite.

Gahl’s study was performed on a small observation hive in which 820 bees were color-marked and uniquely numbered to provide an accurate indication of age. Data collected included the shaking situation (if the bee performed the shaking dance alone, on one other bee, or on several other bees), the age of the shaker, and the age of the bee shaken (if the shaking dance was performed on other/s). Over his 28-day observation, 4949 shaking dances were peformed: 2039 shaking dances were performed alone (41.2%), 2220 were performed on one other bee (44.8%), and 690 were performed straddling more than one bee (14%) (Gahl, 231). Gahl focused on the shaking dances performed one-on-one. (Why he did not look at the other two categories in further detail, I am unsure of.) In regards to correlationship with age, the results were as followed:

The included graph shows the age difference between the shaker and the recipient. A positive number indicates that the shaker was older than the recipient while a negative number indicates that the shaker was younger than the recipient. As you can see, the age difference between the two bees ranged from -9 days and 22 days, with less than 4% of the shaking dances performed on bees older than the shaker. The bees would shake other bees up to 22 days younger than them, however they would not shake any bee older than 9 days.

From this graph, we see that the ages of shakers ranged from 0 to 24 days and the ages of receivers ranged from 0 to 26 days. The majority of shakers were between 9 and 19 days old, while most of the bees that were being shaken were 2 days old. Thus, Gahl’s research shows that “a relationship has been found between the age of the shaker and the bee shaken, the shaker being nearly always older” (Gahl, 232). According to Gahl, shaking is not performed randomly, but with some discrimination determined by age. Some sort of age recognition is taking place within the hive and among the bees. My question is, why have this age recognition? What purpose does it serve? Gahl did not provide any explanations on this other than his results may relate to the function of the shaking dance. In other words, because this shaking dance seems to be driven by certain age-related rules, the purpose of the shaking dance may have something to do with such age discriminations. Is it to train younger, less experienced bees for something? Is it a type of information sharing? Is it a way of exhibiting dominance and therefore establish a type of hierarchy among the bees in the hive? In addition, how do the shakers do this type of age-discrimination? Gahl proposes that the shakers know based on the physiological variation of bees differing in age, traits such as “strength, health, glandular growth, or labour category (which is partially related to age and partially to food conditions in the hive), or some combination of these” (Gahl 232). I wonder if age could also be discriminated by pheromones or other nonvisual cues such as the way the buzz or the pitch at which they buzz.

However, the interesting thing about this article lies in the fact that there is a type of age-discrimination going on, regardless of how this is accomplished or its purpose. This illustrates the intricacies of communication. It is not a simple process that can be generalized over one species. Many things come into play, such as the absolute age of the communicators, and even their ages relative to each other. This is also seen in humans as well. We communicate with people differently based on our ages. There are certain rules to follow when speaking to an elder, and there are particular ways in which we speak to those younger than us. Although much of these rules are socially contrived, communication in itself is a social process.

—————————-UPDATE—————————-
On second thought, could this be just a correlation? Maybe the shaking dance is not discriminatory via age. Instead, it may be something completely separate that is correlated to age. Just a thought.

For humans, dancing can be a form of communication that conveys a lot of nonverbal information. Although we mainly partake in dancing for entertainment reasons, we must not forget that it is guided by social conventions and conceived guidelines. Therefore, our bodies can say a lot more than we think based on how we move. Honeybees, too, use dancing as a means to communicate with one another. Although it is less for entertainment as it is for survival, they follow certain social patterns and expectancies just as humans do. Jacobus Biesmeijer and Thomas Seeley’s research on the waggle dance of honeybees illustrates that honeybees use a form of dance in three situations when foraging for food. The followers of the waggle dance “can use location information acquired from the dance to find the indicated food source” which in turn “contributes to the foraging success of a honey bee colony” (Biesmeijer & Seeley, 133). Information on the type of food (pollen vs. nectar), the direction, and the distance of the food source can be conveyed through this dance. They studied the following three contexts:

1) The novice forager finding its first food source

2) The experienced forager whose foraging expedition has been interrupted

3) The experienced forager that is engaged in foraging

In all three contexts, the honeybee can either use the waggle dance information to guide its search or search independently for a food source without following any dance.

Biesmeijer and Seeley set up an observational hive in which the bees were forced to enter and leave the hive from one side of the cove. Consequently, all of the nectar unloading and all of the dancing could be recorded methodically. They performed three trials of observation: during the spring, summer, and fall. Depending on the trial, thirty or sixty bees were labeled for individual identification. The observer noted the following of a waggle dance if a bee was within one bee length of the dancer, faced the dancer, and moved so that its head always faced the performing dancer. Honeybees that had early excursions shorter than ten minutes and did not unload nectar or pollen upon return (thus performing an orientation flight) were considered novice foragers. The 48 novice foragers were observed from when their attempts of foraging began until when they engaged in successful food collection. Nineteen of those honeybees, or 40%, attempted to forage without the aid of information from any type of waggle dance. Eighteen honeybees, or 37%, relied on the waggle dance of other bees. The remaining 11 honeybees, or 23%, relied evenly on both. It is interesting to note that although there were differences in how the honeybees foraged for food, they did not differ statistically in the number of search trips, around 4.3 trips, required to find their first food source (Biesmeijer & Seeley, 136).

Sixty-three experienced foragers were observed on the 512 days determined as interrupted forager days. The behavior of interest was how the honeybees went back to foraging, if they followed a waggle dance to resume or if they went independently to find the same source. 63% of the time, the bees made trips that were not preceded by the following of a waggle dance, while 37% of the time, the bees made trips preceded by the following of waggle dance (termed reactivation). They found through statistical analysis that success was only slightly (but not significantly) higher for reactivation trips (preceded by the following of a waggle dance) than for trips that were not preceded by the following of a waggle dance (Biesmeijer & Seeley, 137). Looking at the trends over the whole day, experienced foragers followed the waggle dance for 16.6% of their daily trips when there were no interruptions.

When looking at the overall foraging activity for each experienced forager over their lifetime, Biesmeijer and Seeley found that “the percentage of first trips [of the day] by reactivation decreased over days of foraging” for most of the trials (trials 1 and 3)(Biesmeijer & Seeley, 137). In other words, experienced honeybees that lived longer tended to decrease their following of the waggle dance before going out on their first foraging trip of the day.

It is also interesting that Biesmeijer and Seeley found “dance following much more common after a failed trip [. . .] than after a successful one” (Biesmeijer & Seeley, 137). Honeybees that did not follow a waggle dance and failed to find food were 22-33% likely to follow a dance before their next trip. If the honeybees were successful however, that probability of following a waggle dance before their next trip dropped to 6-8%. The same trends were found even for honeybees that did follow a waggle dance initially. Honeybees that followed a waggle dance and failed to find food were 60-80% likely to follow a dance for their next trip. However, if the honeybees were successful in finding food, that probability dropped to 22-44% of following a waggle dance for their next trip (Biesmeijer & Seeley, 138).

After reading the results, let’s revisit the purpose of the study: to examine the extent to which worker honeybees acquire information from waggle dances throughout their careers as foragers (Biesmeijer & Seeley, 139). As a recap, we found that 37% of the novice foragers followed a waggle dance to find their first food source, experienced honeybees followed waggle dances 37% of the time after their foraging was interrupted, and experienced foragers followed dances before 17-20% of their trips, especially if their previous trips resulted in no food.

Biesmeijer and Seeley’s results provide some interesting discussion topics. First of all, although only 37% of novice bees relied on the waggle dance to find their first food source, if no food source were found, they were more likely to follow a waggle dance for their next trip. On average, it took novice honeybees 4.3 trips to find their first food source. Therefore, I hypothesize that if we were to graph the behavior of bees over trips, we would see a slight increase in the following of waggle dances until that 4.3 marker and then a decrease (since the results showed that if successful in finding food, honeybees were less like to follow a dance after). This decrease would continue since the results also showed that experience honeybees who lived longer and gained more experience were less likely to follow waggle dances.

Another topic I would like to discuss is the availability of waggle dances, in other words, how many of the honeybees that knew the location of food sources actually produced a waggle dance. This number would alter how many honeybees followed the dance such that if there was a high availability of dancing bees, the amount of honeybees following the dance would be higher than if there were not that many honeybees producing the waggle dance. In addition, that could say something about the evolutionary history of the waggle dance. The balance between the amount of waggle dance produced and the amount of following would, I assume, be tweaked through evolutionary forces. With too much dancing available, this would take up unnecessary time and energy of the dancing bees which they could be devoting to other tasks. However with too little dancing available, the following of the dance would be inefficient if there were not enough dances to learn from.

I also wonder why such a phenomena occurs if the success of finding food does not differ that greatly between the followers of the dance and those that did not follow the waggle dance. Does this communication system benefit the bees in a different way? Even if both the follower and the non-follower brings back food with the same probability, does following the dance allow the bees to find the food faster? Biesmeijer and Seeley offer the following explanation: recruitment (following the waggle dance) “guides a bee to a much richer food source [. . .] and lets a bee avoid the cost of inspection flights” (Biesmeijer & Seeley, 141). However, they do admit that only through further study will they be able to make a stronger hypothesis regarding the relative benefits of the waggle dance and how it improves the economy of the colony.

As you read the words I have typed, we are engaging in a type of communication. Due to technology, we have many forms of communication that were unfathomable to our ancestors such as text messages, emails, and online blogs such as these. Inarguably, communication is extremely important for our everyday lives and the continuation of our species. Other animals, too, depend on successful communication with each other and have varying systems of communication. While walking to class we may hear birds chirping and not realize the importance of their songs. In fact, forms of communication are not as simple as one may assume. Many factors come into play that allows the environment of a species to guide the evolutionary history of a particular system of communication.

Endler sums up communication nicely saying that animal communication systems have evolved so that individuals can make decisions based upon the behavior, physiology or morphology of others (Endler, 215). However, what are the factors that guide the evolution of such systems? In my blog, I will discuss the following factors in more detail: those that affect the quality of the received and processed signal, those that affect how the signal is generated and emitted, and those that affect how it fares through transmission through the medium. In essence, the “factors that affect signals [. . .] constrain or bias the direction of evolution of signals and signaling systems” (Endler, 215). The phylogenetic history of a species works hand in hand with the geological time a clade spends in the signaling environment to produce a specific type of signaling design.

I argue that the production of a communication signal is of most importance. Why? Because regardless the quality of the receiving system, if the signal produced is not of good quality, then the effectiveness of communication is automatically destroyed. For example, if you have excellent ears but I cannot form coherent sentences, the information does not get past my lips no matter how well you can hear. Many things affect the generation of a signal such as the physics, biophysics and chemistry of the producing signals for example. If it becomes physically impossible for a signal to be produced, then that mode of signaling will not be successful and therefore will not be selected for. Instead, the physical structure of the signal evolves to increase the efficacy of transmission of the message between emitter and receiver (Endler, 215). Efficacy, however, is not as clear cut as it may seem. If a signal is energetically costly, one may assume that that form of communication will be lost or weakened. However, if there are beneficial trade-offs between the present and future fitness for that species, then there can instead be a bias for things like the time, place, or age of the signaling, and that form of communication can exist and continue to evolve.

There is another trade off that is important: that between the amount of information in a signal and the clarity of the signal. (The two components together are referred to as the “quality” of a signal.) An increase in information is usually achieved via an increase in signal complexity or density. However, as the complexity increases, it becomes difficult to prevent “noise” or confusion with both the production and interpretation of the signal. This brings us to the topic of transmission through the medium through which the signal travels. Environmental constraints can favor signaling during times and places at which things like distortion, attenuation, blocking, absorption, reflection, and refraction are minimized. These effects are exacerbated if the signal is complex with a high information density, or when information is transmitted at a high rate (Endler 217).

The environment can affect signaling both in a direct or an indirect manner. For example, the spatial and temporal variation of predation, or climatic and microenvironmental conditions can directly favor signals that maximize emission and transmission of communication signals (Endler, 216). What I find interesting, however, are the indirect effects environment can have. Endler exemplifies this nicely, “some environmental factors do not directly affect the signals but do affect the evolution of the breeding system [. . .] If the breeding [is] limited to a small range of environmental conditions, then this will bias the evolution of signals and signaling behavior to work better under those more specific conditions (Endler, 216).

The reception of a signal is also not as straightforward as it seems. The current adaptive state of the individuals receptor play a huge role in what can and cannot be received. For example, the present state of an animal’s eyes and the information sent to the brain depends on how much light is in the environment. If the animal is in a microenvironment with high light intensity, its visual system will be less effective at distinguishing between darker pattern elements than between lighter pattern elements (Endler, 218). However, if an animal is in a dark microenvironment, it will be less able to distinguish between lighter pattern elements than between darker pattern elements (Endler 218). In essence, “a given receptor does not always transduce signals into neural outputs in the same way,” and instead depends on the environment the signal is sent through.

According to Endler, “the evolution of a communication system involved three suites of traits: the signals, the sensory and cognitive systems used to receive the signals, and the behavior associated with the signaling” (Endler, 220). Because they are all interrelated, they tend to coevolve, and an effect on one will cause an effect on the other two. Communication is not just about one factor or the other. Instead, it is a network that balances these three main components. To sum up this blog post, “the direction of this joint evolution [is] set by the biophysical and energetic conditions of signal emission, environmental conditions which favor clarity of reception, neural conditions which favor the processing of certain kinds of signals or signal components, and the strategies behind signal emission, detection, discrimination, and decision making” (Endler, 222).

This post is just an introduction to animal communication, to provide context and a better understanding of the following blogs. As the quarter unfolds, what was discussed in this blog should be kept in the back of the mind. Animal communication may be taken for granted, however, just in this introduction, we’ve learned that it is far from simple. Its many intricacies must be appreciated when learning about the communication form in different species. Each communication system had an advantage for the species and the environment that species evolved in.

The following is a table of different modes of communication that animals are known to participate in:

The following is a table of some factors that affect the efficacy of communication systems:

Alas, the end of the quarter draws near, yet before we depart on our separate ways, a final post is in order. As the saying goes, we learn something new everyday, and it is quite the poetic notion that we have been learning about learning itself. Specifically, my posts have focused on the effects of instrumental conditioning on behavior in children. As we step back to look at the bigger picture, I will remind you once again of the author and titles of the articles I have discussed in the order they have been presented.

We first dove into the idea the discussion of whether instrumental reward or instrumental punishment was more effective in producing significant and robust behavioral results in children. The articles by Azrin et al. and Richard et al. both revealed evidence that proved reward to be more advantageous. In fact, their studies arose from the lack of efficiency of previous behavioral training methods which incorporated a type of punishment. In the study by Azrin et al., the Urine-Alarm technique punished the child via a loud buzzer whenever the subject wet his or her bed. In the study by Richard et al., a mild electric shock was administered whenever the child displayed self-injurious-behavior. Both methods were not long lasting and took long to treat the undesired behavior. The Dry-Bed technique, which focused on praise whenever the child correctly urinated and avoided wetting his or her bed, and the dispensing of a spoon of apple sauce whenever the child withheld from the self-injurious-behavior both proved to be more successful strategies. Although in both studies there are many confounding variables, they support the idea that reward could be more effective than punishment in certain circumstances.

However, I do want to add that maybe the prior strategies just had low levels of efficiency and they both just so happened to be strategies implementing some type of punishment. Therefore, any other strategy could have proved more effective, whether or not it was one with a rewarding nature. The argument then could be that it was not a matter of reward versus punishment but was an argument between one specific strategy over another. Because we are not able to test these type of experiments in completely controlled situations (for that is the nature of behavioral psychology on humans), it will be impossible to come to any final conclusions. The reason why I bring this up is because the discussion on Conyers et al.’s article exhibited a case where a strategy implementing punishment seemed to be more successful than one implementing reward. This shows that the efficiency of strategies depend on the context and the specific situations. As I mentioned before, one method will not necessarily prove more effective than another across the board or in all types of situations. In learning, there are no such things as golden rules. Each circumstance is unique and therefore requires a type of learning tweaked to its own conditions. In the case of Conyers et al., we have a group setting whereas in the previous two articles, the subject was being attended to individually. Could this be the cause of the disparity? In the studies by Azrin et al. and Richard et al., the subjects were never surrounded by anyone else with the behavioral problem. Only they themselves were the ones being targeted for treatment. However, in the article by Conyers et al., multiple children receiving treatment display disruptive behavior, and therefore, subjects are surrounded by others behaving similarly to them. Subjects then may feel like their disruptive behavior is more “normal” and common than the subjects that wet their beds or participate in self-injurious-behavior.

Later on in the quarter I presented two other studies, that by Magrab & Papadopoulou and Luersen et al., which both focused on the effect of reinforcement (via sticker charts) on children suffering from chronic diseases. These articles stemmed from the patients’ poor adherence to their medical treatment. Although (in our debate on whether reinforcement or punishment is more effect) only reinforcement was tested, I believe that if they were to have tested a punishment type procedure, the punishment would be less effective than the reward. This may be because, as I mentioned before, introducing a reward program gives the patients something to look forward to and want to work for. It introduces something positive in their already adverse and tiresome life. Medical difficulties, especially chronic diseases, not only burden the body but also have significant psychological ramifications. It is not normal for a child to have to go through the demanding treatments, to be restricted from everyday activities, to be constantly worrying about their health. Therefore, giving them some kind of encouragement, something rewarding, something positive is extremely important. These cases are special from everyday conditions so, although it can be argued both ways for which is more effective (reinforcement vs. punishment), I feel that for clinical cases, especially those severe in nature, a reward system would prove triumphant.

As I mentioned before, there are many variables that cause a strategy to have varying levels of success. Another aspect quite important in our discussion involves the therapists or instrumental reinforcers themselves. For these articles, I focused on reinforcement for simplicity purposes and to not confound type of instrumental conditioning with the identity of the reinforcer. The study by Wahler et al. focuses on the mother as being the therapist for her child where the study by Patterson & Anderson focuses on the child’s peers as the social reinforcers. In both, the ultimate behavior of interest is the behavior of the child subjects. However, the behavior that is being directly manipulated is that of the mother and the child’s peers. Can such a strategy transfer a change in behavior from one individual to another? And if so, can this prove to be more beneficial than directly changing the behavior of the subject? These two studies produced data that supported the idea that not only is this type of indirect strategy successful, but it could be more beneficial such that it produces more long term results. To discuss why this proved to be the case, I will remind you that Wahler et al. state that the parents’ “behaviors serve a large variety of stimulus functions” and “compose the most influential part of [the child’s] natural environment.” Therefore, the parents become the “source of eliciting stimuli and reinforcers which [produce] and [maintain] the child’s behavior” (Wahler, 114). In addition, this type of stimuli provided by the parents constantly surrounds the child. If a strategy works in a context that is unnatural for a subject, the resulting change of behavior may not generalize to other contexts and therefore not be long term. In the same way, children spend the majority of their time with their peers, especially as they grow older and become less dependent on parents. This again supports my overlying theme that there are countless things influencing the behavior in children. I stated in one of my previous posts that the importance of learning lies not only in the individual, but in everything that influences the individual as well. Successful behavioral improvement procedures must take into account the whole picture. Learning is not an isolated entity; it is neither straightforward nor simple. Instead, learning is complex, multifaceted, and involves many intricacies that must be acknowledged. With that being said, changing a behavior is a very complicated process in which many dimensions must be taken with serious thought.

Another dimension that varies greatly is the specific characteristics of the reinforcement istelf. Via the studies by Bijou and Hanley et al., we looked at both the patterns of reinforcement and the presence of an embedded reinforcement. First, we saw that varying patterns of reinforcement, also referred to as intermittent reinforcement, produced a desired behavior that was more resistant to extinction than was a behavior produced by continuous reinforcement. I provided some hypotheses why this might be the case:

Hypothesis 1) Because an intermittent type of reinforcement does not reward the subject on every trial, the subject could just assume it is just one of those trials that he or she will not rewarded. They realize that, to be rewarded, they have to endure these trials with no reward and therefore will not be able to tell that they’ve entered an extinction phase or that anything has changed. However, if the continuously reinforced subjects are not rewarded, this is not “normal,” and they realize that something has changed. The “surprise” factor is different.

Hypothesis 2) The intermittent type of reinforcement already establishes a moderate amount of frustration on the subjects. They are a bit upset that they do not receive rewards all the time, but this negative feeling is minor. The continuous type of reinforcement establishes no frustration on the other group of subjects since they are always rewarded. Although once no reward is administered, both group A and group B will be greatly frustrated, the difference between the initial levels of frustration and the final levels of frustration will be different for group A and for group B. Group A will feel a greater change in frustration while group B, already frustrated a bit, will feel a smaller change in frustration.

There are other hypotheses that I would like to mention at this moment that I did not include earlier. These stem from both Professor Blaisdell’s lectures and the Domjan readings.

Hypothesis 3) The children experiencing a partial reinforcement will be conditioned to continue to exhibit a behavior while feeling frustration. The frustration thus turns into the stimulus. Therefore, during the extinction period, the ever-present frustration elicits the continuation of behavior until the subject’s frustration builds up to cause the realization that reward no longer will follow.

Hypothesis 4) The children experience a reward following a nonreinforced trial (since it is a partially reinforced schedule). Therefore, because subjects can remember if trials are reinforced or not (a phenomenon proposed by Eric Capaldi), the nonreinforced trial becomes a cue to continue behavior motivates responding in the hopes of receiving a reinforcement. Similarly to hypothesis 3, this will continue until the exceedingly high level of frustration causes extinction.

The second characteristic of the reinforcement we discussed was that focused on in the study by Hanley et al. We saw that the reinforcement does not have to be directly related to the behavior but may reside in its vicinity via embedded reinforcement. We discussed embedded reinforcement as the reinforcement that attracted the children to the areas in which an increase in participation was desired. Therefore, instead of reinforcing the behavioral participation in these zones, the zones themselves were reinforced. Subject’s received the reward just by being in these areas whether or not they participated in the related activity. This lead to the discussion of a dependence on the probability that once they are in the zones, they will subsequently interact with the activities surrounding them. The data Hanley et al. found proved that this proved to be sufficient enough to change the child’s behavioral preference of the zones and participation in their respective activities. I argued that this proves that reinforcement is such a powerful means that it can even indirectly alter behavior. I would now like to propose that this embedded reinforcement may sometimes prove to be more beneficial in some situations. This type of behavioral manipulation allows for the children to make their own decisions in regards to their behavior without direct manipulation on that particular behavior. Therefore, they are able to choose how they want to behave without the expectation of a reward. Although they are rewarded for being in the vicinity of the activity, they are never rewarded for actually partaking in the activity itself. In a real life setting, reinforcement will not always follow a behavior so training the children not to expect a reward due to the behavior itself can allow the behavior to become more generalized. In other words, subject’s have a choice in the experimental phase (in which the choice to participate in the behavior is not reinforced, just as it would be in an everyday situation) and still choose to partake in a behavior. This can then provide a more accurate setting of the normal situations faced after experimentation trials.

Before I conclude my final post, I would like to discuss how powerful reinforcement can be. We know that it can change behavior; however, we’ve only seen it change behavior into something more positive. The outcome has always been beneficial for the subject and those surrounding individuals. Therefore, the fact that behavior is going from negative to positive can be seen as a sort of push in the direction of a successful outcome. It provides a type of motivation towards the desired result. An argument can be made, then, that the opposite is true too. If the outcome is objectionable and undesireable, this can lead to preexisting resistance against a change in behavior. Therefore, all types of instrumental procedures will face a preliminary obstacle. Would it then be harder for instrumental reward to create a result that is not wanted? According to Billings et al., surprisingly, instrumental conditioning is so powerful that it can even produce outcomes that may be harmful to the subject. He showed how subtle instrumental rewards can cause children to falsely incriminate their own selves. Even if they are aware of the consequences of being guilty, the reinforcement is so strong that it does not matter in the overall picture. The children still admit to things they didn’t do.

In summary, I would like to reiterate the overarching theme and specific points we have learned about. What we should take away from these blog posts is that instrumental conditioning is not something that is clear cut. It is not something that can fit any mold. Instead, it is quite complex and depends on a myriad of influences which include the type of conditioning (reinforcement vs. punishment), the persons involved, the directness of the conditioning (whose behavior is directly conditioned), who the reinforcer is, the pattern of conditioning, and the present situation of the individual, just to name a few. Therefore, to produce a strategy that is successful, all these ingredients must be weighed heavily and must be taken into account seriously. There is so much we do not know about instrumental conditioning because that, as we’ve seen, is the nature of the beast. It is so complex that we probably will never know all that there is to know about it. However, no one can argue against the fact that we are influenced with instrumental conditioning in our everyday lives, whether we are aware of it or not, and that it has made all of us who we are today.

So far, we have only looked at studies that used positive reinforcement to achieve behavior that is something positive for both the subject and those around him or her. This week, we will look at how positive reinforcement can actually produce and increase behavior that may be harmful and even lead to one’s detriment. In the article by Billings et al. we see a study on how “reinforcement can induce children to falsely implicate themselves in wrongdoing” (Billings et al. 125). Their verbal behavior can be manipulated and shaped such that the accuracy of their statements is greatly reduced. Depending on how an interview is conducted, an interviewer can induce false accusations and confessions of wrongdoings. Additionally, these results are robust such that the children “continue to affirm their accusations even when challenged” later on (Billings et al. 126). First let’s look at how such a phenomenon is achieved. We will then look at why this phenomenon may occur.

Ninety-nine 5 to 9-year-olds are introduced to and are allowed to play with a colorful toy in their elementary school. After a span of three days, the experimenters remove the toy and claim that someone has taken the toy, probably just to play with it. They explain that they believe a student is responsible and that they need the children’s help to find out what has happened to it and who has taken it. Each child is then taken separately to be interviewed and is questioned in a “warm, supportive way” (Billings et al. 128). The experimenters manipulate how the children are interviewed such that the control group of children are asked straightforward suggestive questions while the reinforcement group children are approached with the same suggestive questions but with an addition of reinforcement after every question answered with a “yes.” Reinforcement includes verbal responses such as “Thanks!” “Great!” “You’re being a real help.”

There are five groups of interview questions:

1) Filler Question: these questions are expected to produce a “yes” answer. (“Do you remember the Brain Warp toy?”)

2) Guilty Knowledge Questions: these questions ask for information the child cannot possess unless he or she is present when the toy is taken. (“When the kids took the toy, did the toy make a loud noise?”)

3) Direct Witnessing Questions: these questions ask if the child has directly observed the toy as it is taken. (“Did you see the kids take the toy?”)

4) confession Questions: these questions ask if the child has personally participated in the taking of the toy. (“Did you help another kid take the toy?”)

5) Leading correct Questions: these questions ask the child for information that the child does in fact possess. (“Did the toy have different colors?”)

The Guilty Knowledge, Direct Witnessing, and Confession questions are classified as the misleading questions that are potentially self-incriminating. Results are calculated based on the percentage of times the children answer “yes,” either verbally or nonverbally, to one of these three categories of questions. Billings et al. find that the simple reinforcement tactics can in fact “induce children to make false incriminating admissions against themselves” such that 52% falsely admit to guilty knowledge concerting the theft, 30% falsely admit to witnessing it, and 18% falsely confess to participating to the theft with their corresponding control group counterparts resulting in 36%, 10%, and 6% respectively (Billings et al. 133).

Billings et al. also find that “conversations with teachers afterwards [indicate] that the children generally [enjoy] being questioned, even though from a strictly legal viewpoint, they [implicate] themselves in an apparent theft” (Billings et al. 133). Why then are children willing to admit to being part of or being responsible for something negative which may give rise to punishment? Their sense of enjoyment may stem from the fact that this type of reinforcement causes them to feel like they are doing something praiseworthy and honorable at the immediate time frame. In this experiment, it is important to Billings et al. that everything is conducted such that the children have a positive frame of mind and lack any anxiety. Although they are admitting to something that is condoned, they are more focused on their prevalent actions which are prompting praise. Or it could be that due to their limited experience, the children may be failing to recognize that “by making false claims of guilty knowledge or direct witnessing, they [are] thereby implicating themselves in the theft” (Billings et al. 134). Instead, they think that they are just helping and are not realizing the ramifications of their claims. It could also be that they do understand the consequences and are paying attention to both, but merely outweigh the “negative utility of possible self-incrimination [with] the positive utility of receiving praise and approval from the interviewer” (Billings et al. 135). They lack the ability to forego the immediate positive consequences to avoid the more remote negative consequences.

The reason that this is so important is because Billings et al. mention additional studies of adults and adolescents that find similar results. Positive reinforcement and feedback can “induce adult eyewitnesses to make inaccurate statements or report false memories. Older individuals will sometimes even make false self-accusations in response to social pressure and other influences” (Billings et al. 126-127). Although the type of reinforcement and tactics used must differ slightly due to the age differences, this phenomenon still persists. In regards to our legal systems, the consequences for an individual therefore can heavily depend on the interrogation and interview process and the level of experience each individual has. How much conscious control do we actually have then of our outcomes and present situations? In this study, “gentle tactics [. . .] are able to extract self-incrimination admissions from children and even several full confessions in a matter of a few minutes” (Billings et al. 136). Emphasis must be placed on the gentleness of these techniques and the fast manner in which they work. While being questioned, one may not realize how bad a situation they are getting into since the process may seem so demure and safe due to the positive aspect of the rewards. In addition, one may think that nothing consequential can result from a questioning of only a few minutes. This type of positive reinforcement therefore is an enemy in disguise that is harder to reveal than if being interrogated in a harsh, accusatory manner. The limitation for this study, however, is that the crime is a theft-crime. If the crime is instead something more serious, such as breaking the toy, will the results change?

In closing, it is also important to mention of a case where this phenomenon actually happened. In 1998, a 7-year-old and 8-year-old boy were charged for first-degree murder after admitting to killing an 11-year-old girl. Luckily, evidence proved that they could not have possibly been the killers and the charges were dropped. Investigators believed that the interviewers were responsible for the inaccuracies of the boys’ confessions. The interviewers bought the children a Happy Meal and reminded them that “good boys tell the truth [. . .] held their hands, told them they were friends, and questioned them about the murder” (Billings et al. 126). These things could all be seen as positive reinforcement and could have easily manipulated the boys’ statements.